{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "4472ac03-186c-4b8b-b200-0cccd0d56b46",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: https://mirrors.aliyun.com/pypi/simple\n",
      "Requirement already satisfied: requests in /root/miniconda3/envs/python39/lib/python3.9/site-packages (2.29.0)\n",
      "Requirement already satisfied: numpy in /root/miniconda3/envs/python39/lib/python3.9/site-packages (1.23.5)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in /root/miniconda3/envs/python39/lib/python3.9/site-packages (from requests) (3.1.0)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /root/miniconda3/envs/python39/lib/python3.9/site-packages (from requests) (3.4)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /root/miniconda3/envs/python39/lib/python3.9/site-packages (from requests) (1.26.15)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /root/miniconda3/envs/python39/lib/python3.9/site-packages (from requests) (2022.12.7)\n",
      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "! pip install requests numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "744af584-1202-4c44-a1ac-a6b7b3307908",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data: {\"signature_name\": \"serving_default\", \"instances\": ...  [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0]]]]}\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import json,numpy\n",
    "class_names = ['T-shirt/top', 'Trouser', 'Pullover', 'Dress', 'Coat', 'Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot']\n",
    "images = [[[[0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0]], [[0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0]], [[0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0]], [[0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0]], [[0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], 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[0.00392156862745098], [0.0], [0.0], [0.7803921568627451], [1.0], [0.9686274509803922], [0.22745098039215686], [0.0], [0.6313725490196078], [1.0], [0.9882352941176471], [0.4666666666666667], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0]], [[0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.3843137254901961], [0.6235294117647059], [0.2784313725490196], [0.0], [0.0], [0.26666666666666666], [0.6901960784313725], [0.6431372549019608], [0.22745098039215686], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0]]]]\n",
    "images = numpy.array(images)\n",
    "\n",
    "\n",
    "image = images[0]\n",
    "plt.figure()\n",
    "plt.imshow(image)\n",
    "\n",
    "data = json.dumps({\"signature_name\": \"serving_default\", \"instances\": images[0:3].tolist()})\n",
    "print('Data: {} ... {}'.format(data[:50], data[len(data)-52:]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "211d8dff-90f9-414b-929e-8b16d57beefb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import requests\n",
    "headers = {\"content-type\": \"application/json\"}\n",
    "json_response = requests.post('http://mnist-202208011.service:8501/v1/models/mnist:predict', data=data, headers=headers)\n",
    "predictions = json.loads(json_response.text)['predictions']\n",
    "\n",
    "show(0, 'The model thought this was a {} (class {}), and it was actually a {} (class {})'.format(\n",
    "  class_names[np.argmax(predictions[0])], np.argmax(predictions[0]), class_names[test_labels[0]], test_labels[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "1453deb8-8a38-4c2e-9299-48bac7b6791f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'predictions': [[-9.80964851, -12.9484625, -11.6673059, -12.803503, -9.53750706, -1.060938, -8.1383028, 1.6401614, -2.66659474, 4.26639605], [-2.15995264, -18.0709095, 3.3817687, -6.59154129, -1.36319602, -22.9194298, -0.411093801, -29.3422184, -6.84196091, -21.497261], [-7.07187414, 7.57630968, -15.3348751, -3.86331797, -3.77847433, -16.6646538, -10.2554255, -15.0998669, -9.78727245, -17.693224]]}\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# docs_infra: no_execute\n",
    "headers = {\"content-type\": \"application/json\"}\n",
    "res = requests.post('http://mnist-202208011.service:8501/v1/models/mnist:predict', data=data, headers=headers)\n",
    "result = json.loads(res.text)\n",
    "print(result)\n",
    "predictions = result['predictions']\n",
    "\n",
    "for i in range(0,3):\n",
    "  show(i, 'The model thought this was a {} (class {}), and it was actually a {} (class {})'.format(\n",
    "    class_names[np.argmax(predictions[i])], np.argmax(predictions[i]), class_names[test_labels[i]], test_labels[i]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a848c161-11eb-4ee5-8037-7d82e43440ee",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.9",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
